A significant portion of the items sold by a retailer are returned to their stores. A typical brick and mortar store can often expect 8-10% of the items it sells to be returned, while an online store may see returns of nearly 40%. Traditionally, retailers approach this problem by projecting future returns based directly on past returns. However, this and other approaches usually fail to accurately predict the quantity and timing of future returned items, which is undesirable.